The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
When trying to decipher large data sets of information, especially with regards to sensor temperature data in an HVAC (heating, ventilation, air conditioning) monitoring and control system, breaking the large amount of data reported down to a point where the data allows for meaningful and easily determined actions to be taken by an individual entrusted with managing the HVAC system can be difficult. The fact that alert thresholds can be different among various temperature sensors means that the data needs to be normalized before specific action can be taken. Normalizing the sensor signals from hundreds or even thousands of sensors that may be used in a large HVAC system becomes important, particularly as individual sensor values become irrelevant. Individual sensor values become irrelevant when the primary interest of a user who is responsible for monitoring performance of the HVAC system in a given data center or other form of building are the deviations from what the sensor values should be.
Another challenge is presenting the large amount of data to the user in a manner that allows for decisions on modifying set points, changing unit groupings, changing sensor assignments, etc. to be easily determined and implemented by the user. Providing a manner of displaying large amounts of sensor information showing uniformity or lack of uniformity in temperature distribution within a data center or other building or enclosed structure, would be highly important for enabling the user to quickly gauge where cooling resources are being over-utilized with the data center or building, as well as where additional cooling resources are required, and further where cooling resources are being adequately used.